Mobile music recommendations for runners based on location and emotions: The DJ-Running system

被引：19
作者：
Alvarez, P. [1 ]
Zarazaga-Soria, F. J. [1 ]
Baldassarri, S. [1 ]
机构：
[1] Univ Zaragoza, Comp Sci & Syst Engn Dept, Maria de Luna 1,Ada Byron Bldg, Zaragoza, Spain
来源：
PERVASIVE AND MOBILE COMPUTING | 2020年 / 67卷
关键词：
Context-aware applications and services; Music recommendation; Emotions; Geodata integration; Running; PHYSICAL-ACTIVITY; MODEL; ENVIRONMENT;
D O I：
10.1016/j.pmcj.2020.101242
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Music can produce a positive effect in runners' motivation and performance. Neverthe-less, these effects vary depending on the user's location, the emotions that she/he feels at each moment or the type of training session. In this paper, a context and emotion-aware system for the recommendation and playing of Spotify songs is presented. It consists in a location-based mobile application that interacts with a novel emotional wearable and a recommendation service that predicts the next song to be recommended. These predictions are performed by an intelligent system that combines artificial intelligent techniques with geodata and emotionally-annotated music. A wide variety of location-based services and music services available in Internet have been integrated into the recommender in order to support the decision-making process in a real environment. The final solution has been customized to be tested in the city of Zaragoza. (C) 2020 Elsevier B.V. All rights reserved.
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页数：18
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